WO2018183153A1 - Systèmes et procédés de mesure en temps réel de courbure de surface et d'expansion thermique de petits échantillons - Google Patents

Systèmes et procédés de mesure en temps réel de courbure de surface et d'expansion thermique de petits échantillons Download PDF

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Publication number
WO2018183153A1
WO2018183153A1 PCT/US2018/024266 US2018024266W WO2018183153A1 WO 2018183153 A1 WO2018183153 A1 WO 2018183153A1 US 2018024266 W US2018024266 W US 2018024266W WO 2018183153 A1 WO2018183153 A1 WO 2018183153A1
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WIPO (PCT)
Prior art keywords
image
value
sample
laser beam
curvature radius
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PCT/US2018/024266
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English (en)
Inventor
Alexei Ermakov
Xiuyan Li
Eric Garfunkel
Leonard C. Feldman
Torgny Gustafsson
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Rutgers, The State University Of New Jersey
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Application filed by Rutgers, The State University Of New Jersey filed Critical Rutgers, The State University Of New Jersey
Priority to JP2019553955A priority Critical patent/JP2020512564A/ja
Priority to US16/499,588 priority patent/US11248904B2/en
Priority to CN201880036335.5A priority patent/CN110709204B/zh
Publication of WO2018183153A1 publication Critical patent/WO2018183153A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/255—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures for measuring radius of curvature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/2441—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures using interferometry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection

Definitions

  • the present disclosure generally concerns thin film stress measurement. More particularly, the present solution relates to implementing systems and methods for real time measurement of a surface curvature and thermal expansion of samples (even as small as 5mm x 5mm).
  • do is a distance between two laser beams 102, 104 reflected from a sample surface 106 and applied to the detector 108
  • Ad is the difference between the distance do and the distance d between the two reflected laser beams 110, 112 resulting from the deflection of the laser beams 102, 104
  • L is a distance between a detector 108 and the sample surface 106
  • ⁇ is the laser beams' deflection angle (as schematically shown in FIG. 1).
  • the present disclosure generally concerns systems and methods for measuring a curvature radius of a sample.
  • the methods comprise: emitting a light beam from a laser source in a direction towards a beam expander; expanding a size of the light beam emitted from the laser source to create a broad laser beam; reflecting the broad laser beam off of a curved surface of the sample; creating a plurality of non-parallel laser beams by passing the reflected broad laser beam through a grating mask or a biprism; using the plurality of non-parallel laser beams to create an interference pattern at a camera image sensor; capturing a first image by the camera image sensor; and processing the first image by an image processing device to determine the curvature radius of the sample.
  • the curvature radius can be used to compute a measurement of stress in the sample.
  • the curvature radius is determined by: performing operations by the image processing device to determine a value a based on contents of the first image and contents of a second image produced by light reflected off of a flat surface or a curved surface prior to a stress inducing treatment; determining a laser beam divergence value using the value a; and using the laser beam divergence value to compute the curvature radius of the sample.
  • the value of a is determined based on positions of bright features contained in the first image and the second image. More particularly, the value a is determined by: extracting a first center position for each bright feature contained in the first image and a second center position for each bright feature contained in the second image; plotting points on a two dimensional graph for each said first center position respectively as a function of each said second center position; and determining a slope of a linear line defined by the points.
  • the value of a is determined based on spatial frequency changes of bright features contained in the first image and the second image.
  • the value a is determined by: determining a first frequency of a sinusoidal signal generated using brightness values of the bright features contained in the first image; and determining a ratio of the first frequency to a second frequency of a sinusoidal signal generated using brightness values of the bright features contained in the second image.
  • the grating mask comprises periodic holes and/or periodic lines.
  • the sample may be located inside of a high- temperature furnace.
  • FIG. 1 is an illustration that it useful for understanding how a radius of a curvature is measured in accordance with conventional solutions.
  • FIGS. 2A-2B (collectively referred to herein as "FIG. 2") provide a simplified schematic diagram of an illustrative system for an ex-situ measurement at room temperature.
  • FIG. 3 provides an illustration that is useful for understanding how an image is processed and a curvature is calculated.
  • a small change in divergence of a reflected laser beam can be extracted and the large curvature radius can be calculated.
  • FIG. 4 provides illustrations showing three types of 1-d and 2-d grating masks and the diffraction effects of masks creating several non-parallel laser beams which form interference patterns.
  • FIG. 5 provides an illustration that is useful for understanding how interference patterns of diffracted laser beams form in implementing the present solution.
  • ACTIVE ⁇ 53522986.vl-3/2/18 beam after reflection from the sample surface passes through a mask.
  • Diffracted laser beams interfere with each other and create repeated images of the mask at periodic specific distances where an image is acquired.
  • the reflected beam can be treated as the diverging beam coming from a focal point at a distance F.
  • FIG. 6 provides an illustration showing that a mask can be replaced by a biprism (note that an image sensor can be placed anywhere in the area of the shaded region).
  • FIG. 7 provides an illustration showing two methods to extract the laser divergence using image processing.
  • the position of each feature e.g., bright spot or line
  • the slope of linear fitting a is calculated.
  • the spatial frequency of the bright features is calculated using a Fast Fourier Transform ("FFT") procedure. The ratio of frequency from the flat surface to that from the curved surface gives the value of a.
  • FFT Fast Fourier Transform
  • FIG. 8 provides an interference image of a laser beam reflected from a sample surface and diffracted passing through a line, square hole and circular hole masks, respectively.
  • FIG. 9 provides an illustration showing test results of the present solution using a standard convex mirror with a curvature radius of seven point two meters (7.2m) and an Si0 2 /Si sample in which the stress in Si0 2 and thickness of Si0 2 and Si are known.
  • FIG. 10 provides an illustration showing test results of Si0 2 /SiC samples with different Si0 2 thicknesses tf.
  • R is inverse proportional to tf, resulting in constant stress.
  • Si0 2 film thinner than twenty-five nano-meters (25nm) film stress increases with decreasing film thickness.
  • FIG. 11 illustrates a system for an in- situ/real- time measurement during high temperature processing.
  • FIG. 12 provides an illustration showing a design of sample holder which can hold a sample perpendicularly.
  • FIG. 13 provides a graph showing test results during silicon oxidation. 900, 1000, 1100°C growth temperatures are employed. The R change is faster in the initial stage and slower at lower temperature.
  • FIG. 14 is a flow diagram of an illustrative method for the measurement of stress and curvature of a sample.
  • the present document generally concerns systems and methods for curvature measurement with high resolution of small samples both at room temperature and during high temperature processing.
  • the present solution enables the measurement of the thermal expansion of transparent samples.
  • the present solution is capable of performing curvature measurement with high resolution ( ⁇ down to 4xl0 "6 ) of small samples (as small as 5mm x 5mm) by making use of interference and diffraction effects of a reflected laser beam, combined with novel image processing algorithms.
  • the measurement can be performed at room temperature (ex-situ measurement) or during high temperature processing (in- situ/real-time measurement).
  • Each implementing system includes a laser source, a beam expander, a sample holder, a mask, a Charge Coupled Device (“CCD”) camera, and image processing software.
  • An expanded laser beam with a diameter of six millimeters (6mm) reflected from the sample surface, interacts with a two dimensional (2-d) or one dimensional (1-d) diffraction grating mask so as to form multiple non-parallel laser beams.
  • the laser beams form an interference pattern at a CCD camera sensor located at a specific distance from the 2-d or 1-d diffraction grating mask.
  • image analysis a small divergence of a reflected laser beam is determined accurately from interference patterns.
  • the curvature of the sample surface is also calculated. This implementing system has been tested with Si0 2 /Si and Si0 2 /SiC samples.
  • the implementing system also allows detecting the interference of reflected laser beams from two sides of a transparent sample, which enables measurement of thermal expansion during heating or cooling.
  • System 200 is generally configured to perform a curvature measurement with high resolution of small samples both at room temperature and during high temperature processing.
  • System 200 comprises a laser source 202, a beam expander 204, a sample holder 206, a grating mask 208, a CCD camera image sensor 210, and an image processing device 212.
  • Each of the listed components 202-210 is well known in the art, and therefore will not be described herein. Any known or to be known laser source, beam expander, sample holder, grating mask, and/or CCD camera image sensor can be used herein without limitation.
  • the laser source 202 is generally configured to emit light through a process of optical amplification based on a stimulated emission of electromagnetic radiation.
  • the beam expander 204 is generally configured to expand the size of a collimated beam of light.
  • the sample holder 206 is generally configured to structurally support and hold a sample 222 (e.g., an Si0 2 /Si sample and an Si0 2 /SiC sample).
  • the grating mask 208 comprises a 1-d or 2-d diffraction grating with a periodic structure that splits and diffracts light into several beams traveling in different directions.
  • the CCD camera image sensor 210 is generally configured to generate sense data for an image produced by light reflected from a surface, and provide the sense data to
  • the image processing device 212 can include, but is not limited to, a desktop computer, a personal computer, a general purpose computer, a laptop computer, and/or a smart device.
  • FIG. 2B A more detailed block diagram of the image processing device 212 is provided in FIG. 2B. FIG. 2B is described in detail below.
  • laser light 224 from the laser source 202 is expanded to a parallel broad laser beam 226 (e.g., a beam with a diameter of six millimeters (6mm)) through the beam expander 204.
  • the parallel broad laser beam 226 is reflected from a surface of the sample 222 structurally supported by the sample holder 206 with an incidence angle of ⁇ °.
  • the reflected laser beam 228 then passes through the grating mask 208 forming several non-parallel laser beams 214.
  • the non-parallel laser beams 214 form an interference pattern image at the CCD camera image sensor 210.
  • the CCD camera image sensor 210 generates sensor data for a first image 304 produced by light reflected from a curved surface 216.
  • the first image 304 associated with the curved surface 216 is compared with a previously acquired second image 302 associated with the flat surface or the curved surface prior to a stress inducing treatment.
  • a laser beam divergence is determined based on the results of the comparison. The manner in which the value of a is determined is described in detail below. At this time, it should be understood that the quantity a- 1 is defined by the following Mathematical Equation (3).
  • xo is a distance between two bright spots 308 at the grating mask 208 or at the distance Y from the grating mask and obtained using the flat surface
  • Ax is the difference between the distance xo and a distance ⁇ between the two bright spots to the CCD camera image sensor 210 at the distance Y from the grating mask (as shown in FIG. 3).
  • the quantity a-1 is used to compute the curvature radius R of the sample 222.
  • Mathematical Equation (2) is rewritten as the following Mathematical Equation (4). — (4)
  • FIG. 3 provides an illustration that is useful for understanding this process.
  • a multi-laser-beam method has been described in U.S. Patent Nos. 7391523B 1 and 5912738A.
  • the parallel multi-laser beams are obtained using an optical device etalon.
  • diffraction and interference effects among the parallel multi- laser beams are undesirable because they limit minimum spot size, degrade image quality and must be avoided.
  • the diameter of each parallel multi- laser beam is required to be large enough to minimize the diffraction effects, and therefore the number of parallel multi- laser beams is limited.
  • non-parallel beams 214 are produced by means of diffraction using a grating mask 208 instead of an optical etalon device, and the pattern is formed by interference effects among the non-parallel laser beams 214.
  • the size of the spots 308 in the images 302, 304 can be much smaller, and the number of spots can be much larger than in the conventional methods.
  • the grating mask 208 can be a 1-d or 2-d grating.
  • the dimensions of diffraction can be controlled by different arrays of holes 404 or lines 402.
  • the laser beam 228 is split into several beams 214 as described by a diffraction grating defined by the following Mathematical Equation (5).
  • ⁇ is the angle between the diffracted beam and the grating's normal vector
  • JC is the distance between neighboring lines or holes in the grating mask
  • ⁇ is a laser wavelength
  • m is an integer representing a propagation mode of interest.
  • m 0, +1, -1 is considered.
  • the split laser beams 214 form repeating interference images at specific periodic distances from the grating mask 208 in accordance with Mathematical Equation (6), as shown in FIG. 5.
  • the CCD camera image sensor 210 is set near the specific position 504 with a distance Y lake from the grating mask 208, which provides sharpest interference pattern.
  • F includes both diverging effects from the sample surface 222 and from the laser source 202.
  • the center position 704 of each bright spot/line 702 is extracted via parabolic fitting of the brightness values.
  • Parabolic fitting techniques are well known in the art, and therefore will not be described herein in detail. Any known or to be known parabolic fitting technique can be used herein without limitation.
  • the parabolic fitting process generally involves: fitting brightness values to a parabola; and using a parabolic function to determine a location of a maximum brightness value in a given area to establish a centroid of the laser intensity.
  • This process determines the precise value of xo and ⁇ , which defined a y-axis value for a dot (or point) position on a two dimensional graph 710.
  • This parabolic fitting process is repeated for a corresponding bright spot/line for the image 706 associated with a flat surface to obtain another values for xo and ⁇ , which define an x-axis value for the dot position in the two dimensional graph 710.
  • a dot or point is then plotted on the two dimensional graph 710 for the center position 704 of each bright spot 702 contained in a given surface image 700 or 708 as a function of that from a flat surface image 706, i.e., using the determined y-axis and x-axis values.
  • the result of the plotting operations is a linear line 712 or 713.
  • the slope of the linear line 712 or 713 gives the value of a.
  • the linear line 712 or 713 is defined by the following Mathematical Equation (7).
  • y mx + b (7)
  • y is the y-axis value of a given dot forming the line
  • JC is the x-axis value of the given dot forming the line
  • b is the y-intercept value of the line (i.e., where the line crosses the y-axis).
  • the brightness values of each spot 716 are fitted as a sine function using an FFT.
  • FFT techniques are well known in the art, and therefore will not be
  • Any known or to be known FFT process can be used herein without limitation.
  • the brightness values are used as inputs for a standard FFT algorithm.
  • the ratio of frequency from a flat surface image 722 to a frequency from a curved surface image 720, 724 gives a value of a.
  • a is defined by the following
  • the mask can be replaced by a biprism 606, as shown in FIG. 6.
  • the interference fringes from laser beams refracted by both sides of the prism form an image as also shown in FIG. 6.
  • the R calculation is the same.
  • the advantage of biprism 606 in comparison to the grating mask 208 is that the CCD camera image sensor 210 can be set anywhere in an area of region 604, instead of periodic fixed positions Yong. Therefore, the biprism 606 based solution does not require position adjustments for different curvatures.
  • the novel image fitting methods provide an accuracy improvement.
  • the resolution can be estimated depending on image fitting and camera pixel size. Take a camera of 640x480 pixel resolution with a sensor size of 6mmx4mm (9x8 ⁇ pixel size) and Y of lm for an example, 9 ⁇ distance could be distinguished by two data points and a fitting can identify less than half of it, resulting in a divergence angle ⁇ measurement accuracy better than 4xl0 "6 . Even better measurement accuracy can be easily achieved when using higher resolution camera sensors.
  • the present solution has been tested using a standard convex mirror with a curvature radius of 7.2m and using a Si0 2 /Si sample for which the curvature radius is calculated based on known stress in Si0 2 , and thickness of both Si0 2 and Si substrate.
  • the test results are shown in FIG. 9.
  • the results for a Si0 2 /SiC samples has been also obtained for the first time as shown in FIG. 10.
  • the curvature radii above 100 m in case of ultra-thin films are accurately determined and the resulted stress distribution in Si0 2 film is consistent with theoretical expectation.
  • Placement of a grating mask 208 (or a biprism 606) between the sample 222 and the CCD camera image sensor 210 allows positioning of the sample at substantial distance from the laser source 202 and other optical elements, which enables in-situ measurements when the sample is located inside of a furnace or other sample-processing apparatus.
  • other existing methods use optics to create multiple laser beams before they get
  • FIG. 11 An illustration of an illustrative system 1100 architecture implementing the present solution for an in-situ measurement of curvature during high temperature processing is provided in FIG. 11.
  • a sample is perpendicularly fixed by a perpendicular sample holder 1106 in an alumina tube 1110 in a furnace 1108.
  • An illustrative architecture for the perpendicular sample holder 1106 is provided in FIG. 12.
  • the expanded laser beam incidents the sample surface with a normal angle ⁇ 0 through a quartz window 1102 which is fixed to the alumina tube 1110 by a metal connector 1104.
  • the reflected laser beam is adjusted to come out from the alumina tube 1110 through the quartz window 1102 and then is diffracted by the grating mask 208.
  • the distance L between grating mask 208 and CCD camera image sensor 210 can be adjusted by a mirror 1112.
  • the change of curvature radius of silicon substrate during silicon oxidation at 900, lOOOC, 1100°C under latm 0 2 flowing has been measured.
  • the results show a smooth change with time at each temperature.
  • the present solution also enables measuring the thermal expansion of a transparent substrate.
  • the incident laser is reflected from both front and back surfaces of a substrate.
  • the two reflected beams interfere with each other.
  • the condition for constructive interference is obtained in accordance with Mathematical Equation (9).
  • n s refractive index of substrate and p is an integer. While during heating/cooling, the thermal expansion changes substrate thickness t s resulting in periodic constructive and destructive interference.
  • Thermal expansion coefficient a can be calculated in accordance with Mathematical Equation (10).
  • FIG. 2B there is provided a detailed block diagram of an illustrative architecture for the image processing device 212 of FIG. 2A.
  • Image processing device 212 may include more or less components than those shown in FIG. 2B. However, the components shown are sufficient to disclose an illustrative embodiment implementing the present solution.
  • the hardware architecture of FIG. 2B represents one embodiment of a representative computing device configured to facilitate an improved method for the measurement of stress and curvature of a sample. As such, the image processing device 212 of FIG. 2B implements at least a portion of a method for the measurement of stress and curvature in accordance with the present solution.
  • the hardware includes, but is not limited to, one or more electronic circuits.
  • the electronic circuits can include, but are not limited to, passive components (e.g., resistors and capacitors) and/or active components (e.g.,
  • the passive and/or active components can be adapted to, arranged to and/or programmed to perform one or more of the methodologies, procedures, or functions described herein.
  • the image processing device 212 comprises a user interface 252, a Central Processing Unit (“CPU") 256, a system bus 254, a memory 258 connected to and accessible by other portions of the image processing device 212 through system bus 254, and hardware entities 268 connected to system bus 254.
  • the user interface can include input devices (e.g., a keypad 260) and output devices (e.g., speaker 262, a display 264, and/or light emitting diodes 266), which facilitate user-software interactions for controlling operations of the image processing device 212.
  • Hardware entities 268 perform actions involving access to and use of memory 258, which can be a RAM, a disk drive and/or a Compact Disc Read Only Memory (“CD-ROM").
  • Hardware entities 268 can include a disk drive unit 276 comprising a computer-readable storage medium 278 on which is stored one or more sets of instructions 270 (e.g., software code) configured to implement one or more of the methodologies, procedures, or functions described herein.
  • the instructions 270 can also reside, completely or at least partially, within the memory 258 and/or within the CPU 256 during execution thereof by the image processing device 212.
  • the memory 258 and the CPU 256 also can constitute machine-readable media.
  • machine-readable media refers to a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions 270.
  • machine-readable media also refers to any medium that is capable of storing, encoding or carrying a set of instructions 270 for execution by the image processing device 212 and that cause the image processing device 212 to perform any one or more of the methodologies of the present disclosure.
  • the hardware entities 268 include an electronic circuit (e.g., a processor) programmed for facilitating for the measurement of stress and curvature in accordance with the present solution.
  • the electronic circuit can access and run an image processing application 272 installed on the image processing
  • the software application 272 is generally operative to: derive a stress and a sample surface curvature from images formed by means of interference of laser beams diffracted by a grating mask; derive said stress and a sample surface curvature from images formed by means of interference of laser beams refracted by a biprism; determine position changes of bright spots or lines shown in the images; calculate the sample surface curvature using the determined position changes; determine spatial frequency changes of the bright spots or lines shown in the images; and/or calculate the sample surface curvature using the determined spatial frequency changes.
  • Other functions of the software application 272 are apparent from the above discussion.
  • Method 1400 begins with 1402 and continues with 1404 where a light beam (e.g., light beam 224 of FIG. 2A) is emitted from a laser source (e.g., laser source 202 of FIG. 2A) in a direction towards a beam expander (e.g., a beam expander 204 of FIG. 2A).
  • a beam expander e.g., a beam expander 204 of FIG. 2A.
  • the beam expander creates a parallel broad laser beam (e.g., laser beam 226 of FIG. 2) by expanding the size of the light beam emitted from the laser source.
  • the parallel broad laser beam is reflected off of a sample surface with an incidence angle of ⁇ °, as shown by 1408.
  • a plurality of non-parallel laser beams are created by passing the reflected laser beam (e.g., reflected laser beam 228 of FIG. 2A) through a grating mask (e.g., grating mask 208 of FIG. 2A).
  • the non-parallel laser beams are used in 1412 to form an interference pattern at a camera's image sensor (e.g., CCD camera image sensor 210 of FIG. 2A).
  • the camera generates sense data in 1414.
  • the sense data includes sense data for a first image (e.g., image 304 of FIG. 3) produced by light reflected from a curved surface.
  • the sense data is communicated from the camera to an image processing device (e.g., image processing device 212 of FIG. 2A).
  • the image processing device performs operations to determine a value of a based on results of a comparison of the first image to a previously acquired second image (e.g., image 302 of FIG. 3) produced by light reflected from a flat surface.
  • a previously acquired second image e.g., image 302 of FIG. 3
  • the manner in which the value of a is determined is described above in relation to FIG. 7.
  • the value of a is determined by: extracting a first center position (e.g., center position 704 of FIG. 7) for each bright feature (e.g., spot 702 of FIG. 7) contained in the first image (e.g., image 700 or 708 of FIG. 7) and a second center position for each bright feature contained in the second image (e.g., image 706 of FIG. 7); plotting dots (e.g., dot 714 of FIG. 7) on a two dimensional graph (e.g., graph 710 of FIG.
  • the value of a is determined by: determining a first frequency (e.g., frequency fo of FIG. 7) of a sinusoidal signal (e.g., sinusoidal signal 732 of FIG. 7) generated using brightness values of bright features (e.g., spots 716 of FIG. 7) contained in the first image (e.g., image 722 of FIG. 7); determining a ratio of the first frequency to a second frequency (e.g., frequency f s of FIG.
  • a sinusoidal signal (e.g., sinusoidal signal 730 or 734 of FIG. 7) generated using brightness values of bright features contained in the second image (e.g., image 720 or 724 of FIG. 7); and setting the value of a to the value of the ratio.
  • the value of a is used in 1420 to determine a laser beam divergence value a-1.
  • the laser beam divergence value is used in 1422 to compute a curvature radius of the sample. This computation is performed in accordance with the above provided Mathematical Equation (4).
  • the curvature radius is used to compute a measurement of stress in the sample.
  • Mathematical Equation (1) can be used in 1424. Subsequently, 1426 is performed where method 1400 ends or other processing is performed (e.g., return to 1402).

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Abstract

L'invention concerne des systèmes et des procédés permettant de mesurer un rayon de courbure d'un échantillon. Les procédés consistent à : émettre un faisceau lumineux à partir d'une source laser en direction d'un dilatateur de faisceau; étendre une taille du faisceau lumineux émis par la source laser pour créer un faisceau laser large; réfléchir le faisceau laser large hors d'une surface incurvée de l'échantillon; créer une pluralité de faisceaux laser non parallèles en faisant passer le faisceau laser large réfléchi à travers un masque de réseau ou un biprisme; utiliser la pluralité de faisceaux laser non parallèles pour créer un motif d'interférence au niveau d'un capteur d'image de caméra; capturer une première image par le capteur d'image de caméra; et traiter la première image par un dispositif de traitement d'image pour déterminer le rayon de courbure de l'échantillon.
PCT/US2018/024266 2017-03-29 2018-03-26 Systèmes et procédés de mesure en temps réel de courbure de surface et d'expansion thermique de petits échantillons WO2018183153A1 (fr)

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JP2019553955A JP2020512564A (ja) 2017-03-29 2018-03-26 小サンプルの表面曲率および熱膨張のリアルタイム測定のためのシステムと方法
US16/499,588 US11248904B2 (en) 2017-03-29 2018-03-26 Systems and methods for real time measurement of surface curvature and thermal expansion of small samples
CN201880036335.5A CN110709204B (zh) 2017-03-29 2018-03-26 小样品曲率半径和热膨胀实时测量系统和方法

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WO2021128517A1 (fr) * 2019-12-23 2021-07-01 深圳市速普仪器有限公司 Appareil de mesure de rayon de courbure et procédé de mesure de rayon de courbure

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